Generalized Linear Model

#gdp_rightsbased$SpeciesCat <- factor(gdp_rightsbased$SpeciesCat)

itq_glm <- glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial", data = gdp_rightsbased)
itq_glm
## 
## Call:  glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial", 
##     data = gdp_rightsbased)
## 
## Coefficients:
## (Intercept)  current_gdp   SpeciesCat  
##  -1.435e+00    9.518e-05   -9.519e-02  
## 
## Degrees of Freedom: 289 Total (i.e. Null);  287 Residual
## Null Deviance:       320.5 
## Residual Deviance: 195.5     AIC: 201.5
summary(itq_glm)
## 
## Call:
## glm(formula = i_right ~ current_gdp + SpeciesCat, family = "binomial", 
##     data = gdp_rightsbased)
## 
## Deviance Residuals: 
##      Min        1Q    Median        3Q       Max  
## -2.08034  -0.51602  -0.15462  -0.02795   2.71930  
## 
## Coefficients:
##               Estimate Std. Error z value Pr(>|z|)    
## (Intercept) -1.435e+00  1.151e+00  -1.247    0.212    
## current_gdp  9.518e-05  1.562e-05   6.095 1.10e-09 ***
## SpeciesCat  -9.519e-02  2.335e-02  -4.076 4.58e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 320.55  on 289  degrees of freedom
## Residual deviance: 195.45  on 287  degrees of freedom
## AIC: 201.45
## 
## Number of Fisher Scoring iterations: 6

F/Fmsy vs. B/Bmsy for all fisheries